Strong, M., Oakley, J. and Chilcott, J. (2012) Managing structural uncertainty in health economic decision models: a discrepancy approach. Journal of the Royal Statistical Society, Series C (Applied Statistics), 61 (1). pp. 25-45. ISSN 0035-9254
Abstract
Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for quantifying uncertainty due to inadequacies in model structure are less well developed. We introduce an example of a model that aims to predict the costs and health effects of a physical activity promoting intervention. Our goal is to develop a framework in which we can manage our uncertainty about the costs and health effects due to deficiencies in the model structure. We describe the concept of `model discrepancy': the difference between the model evaluated at its true inputs, and the true costs and health effects. We then propose a method for quantifying discrepancy based on decomposing the cost-effectiveness model into a series of sub-functions, and considering potential error at each sub-function. We use a variance based sensitivity analysis to locate important sources of discrepancy within the model in order to guide model refinement. The resulting improved model is judged to contain less structural error, and the distribution on the model output better reflects our true uncertainty about the costs and effects of the intervention.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2012 Royal Statistical Society. This is an author produced version of a paper subsequently published in Journal of the Royal Statistical Society, Series C (Applied Statistics). Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | computer model, elicitation, health economics, model uncertainty, sensitivity analysis, uncertainty analysis |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > Section of Public Health (Sheffield) The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematics and Statistics (Sheffield) |
Funding Information: | Funder Grant number MRC G0601721 |
Depositing User: | Dr Mark Strong |
Date Deposited: | 07 Mar 2012 16:05 |
Last Modified: | 16 Nov 2015 11:49 |
Published Version: | http://dx.doi.org/10.1111/j.1467-9876.2011.01014.x |
Status: | Published |
Publisher: | Royal Statistical Society |
Refereed: | Yes |
Identification Number: | 10.1111/j.1467-9876.2011.01014.x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:43703 |